LLM-based multi-agent systems (MAS) engage tools, share memory, and delegate tasks, often encountering adversarial content. Current defenses for MAS are typically evaluated in isolation, focusing on one attack type at a time, which can lead to costly and hard-to-audit outcomes. This study organizes defenses into five p...
Shaswata Mitra, Raj Patel, Subash Neupane et al.· 0 citations
Overall, developer-reported SST challenges extend beyond vulnerability detection and include workflow, configuration, interpretation, and remediation concerns and can help researchers, practitioners, educators, and tool providers improve SST usability, documentation, result interpretation, and remediation support.
Md Erfan, A. Ryan, Md. Rayhanur Rahman· 0 citations
This pilot study evaluated six open-weight LLMs on the same 100 theorems from CoqStoq, a benchmark derived from real Coq projects and did not statistically test whether one model outperforms another, therefore, the results do not establish a universal ranking of the six models.
A. Ryan, Md Erfan, Akond Ashfaque Ur Rahman et al.· 0 citations
The results show that build integration, not candidate generation or fuzzing, is the primary barrier to reliable LLM-assisted dynamic analysis of full autonomous-vehicle software stacks.
This work constructs a dataset called CAV-STIXGen that maps CAV vulnerability descriptions to STIX domain objects, and analyzes CWE and MITRE ATT&CK co-occurrences to identify recurring threat patterns in the CAV domain, demonstrating how AI-assisted vulnerability-to-STIX translation can automate threat intelligence an...
Md Erfan, A. Ryan, Md. Kamal Hossain Chowdhury et al.· 0 citations
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